Traditionally, a manual process was utilized to determine system performance metrics and related optimization strategies for building systems such as a heating, ventilation and air conditioning (HVAC) systems. This manual process included manual collection of the HVAC system's performance data sets and a manual analysis and evaluation of which strategy to select. During this manual process a field engineer would visit the site of the HVAC system and manually record system parameters (e.g. temperatures, energy consumption, fans speed, etc.) from the actual HVAC system. The data would then be recorded on forms and other tallying documents. In some situations, the HVAC system may have been associated with a building automation system such that the field engineer could extract system parameters from the Building Automation System (BAS). Such system parameters were typically provided via paper reports or electronic reporting means. This manually collected information would then be either manually analyzed or feed into separate analysis system to determine if and how the system could be modeled or possibility optimized. From that point the system's optimization and analysis was based strictly on the single statically collected data set.
While the above manual processes for determining HVAC and other building system performance metrics and related optimization strategies could be somewhat effective, they tended to be inefficient and limited based on the use of limited data. Accordingly, it would be desirable to provide a system and method that more easily and efficiently determined performance metrics and optimization strategies for an HVAC system and other building systems.